Random blog posts about research in political communication, how people learn or don't learn from the media, why it all matters -- plus other stuff that interests me. It's my blog, after all. I can do what I want.

Wednesday, November 19, 2014

Driving Alone

We've all seen the long commute data, but here I'm going to focus on a similar but related measurement -- people who commute the longest, and who drive alone. Using data from this site, I ranked the counties in terms of people who drive alone to work, for the longest period. Why? Because commuting is considered bad for your physical and mental health -- and doing so alone is considered even worse. That's why it's measured in the first place.

Okay, you'd think counties near L.A., in California, or perhaps the greater Atlanta metroplex, would dominate the list. You'd be wrong. Survey says:

Okay, I'm bored typing. You get the idea. The Colorado counties serve Denver, the Kentucky county is the smallest in the state and is roughly halfway between Cincinnati and Lexington, Ky. There are a lot of Virginia counties high on the list, mostly around D.C. But coming in at 14th is New York if that makes you feel any better. Twenty-nine counties list an hour or longer of a commute alone.

Okay, but is a long commute alone really a bad thing?

Let's take Elbert County, Colorado. It's only in the second quartile when it comes to "poor mental health days" ranks in the lowest (best) quartile in "poor physical health days." In other words, you can't easily draw a connection, at least not with one relatively well-off county. To really do this, we need to correlate all the county scores on mental and physical health with time commuting alone. That's a bit more challenging. See below:

Correlation of Minutes Commuting Alone With...

Poor Mental Health Days: r = .21

Lack Physical Activity: r = .34

So there is a correlation between minutes commuting alone and physical and mental health. As one increases, so does the other. But correlation is not causality. To really do this, we need to statistically control for other possible explanatory factors. For example, the number of kids in poverty is also correlated with long lonely commutes (r = .46), but there's no reason to believe they're related. Hell, I even found a small correlation between commuting alone and the percent of people in a county with sexually transmitted diseases (r = .06). I'm willing to bet they're also unrelated (then again ...)

If I really get bored, I may tackle a multivariate approach. But I'd have to be really really bored. It's not a terribly difficult job if I fold the data into SPSS, but I have a long list of other data projects waiting my attention, so feeding this blog is not a priority. My hunch is there is a small yet statistically significant relationship between long, lonely commutes and mental/physical health, but it's modest at best once you control for all the other factors, such as poverty.